A new method to correct systematic errors in ocean subsurface data

A homogeneous, consistent, high-quality in situ temperature dataset covering a period of decades is crucial for the detection of climate changes in the ocean.

Systematic errors in the global archive of temperature profiles pose a significant problem for the estimation and monitoring of the global ocean heat content, a most reliable indicator of climate change. During almost four decades between 1940-1970s, the majority of temperature observations in the ocean within the upper 200 meters was obtained by means of mechanical bathythermograph (MBT). Actually MBT contributes to 68% of ocean subsurface data within 1940-1966.

The new study by Viktor Gouretski and Cheng Lijing from the Institute of Atmospheric Physics (IAP) of the Chinese Academy of Sciences investigated the quality of MBT data by comparing them with reference profiles obtained by means of Nansen bottle casts and Conductivity-Temperature-Depth (CTD) profilers. The study was published in Journal of Atmospheric and Oceanic Technology.

This comparison revealed significant systematic errors in MBT data. The MBT temperature bias was as large as 0.2°C before 1980 on the global average and reduced to less than 0.1°C after 1980. To eliminate this bias from the original data, a new empirical correction scheme for MBT data was derived, where the MBT correction is country-, depth-, and time-dependent.

Several bias correction schemes were tested. In order to objectively assess the performance of the schemes, four metrics were introduced for each correction scheme and bias reduction factors were calculated. The scheme accounting for the depth bias and the thermal bias showed the best performance, significantly reducing the original bias.

Further, the new MBT correction scheme suggests a better performance compared with three MBT correction schemes proposed earlier in the literature (from Japan, United States of America and Germany).

The reduction of the biases increases the homogeneity of the global ocean database. It is important for climate change related studies, such as the improved estimation of the ocean heat content changes.

"This new technique will be used in IAP ocean gridded temperature product and ocean heat content estimate in 2020," said CHENG. "We expect it to significantly improve their quality during the 1940-1970 period."